From Campus Experiment to Campuswide AI: How One Ivy League University Brought GenAI to Its Entire Community with FoundationaLLM

By Peter Kurkowski | April 18, 2025

Empower Every Mind: Unleash AI Across Campus.

Universities are under pressure to innovate—but when it comes to AI, many face the same blockers as enterprises: long timelines, unclear governance, and a lack of infrastructure that balances usability with institutional control.

One Ivy League university, serving a diverse community of nearly 15,000 students, decided to change that.

In just a few weeks, they launched a campuswide AI platform designed to support faculty, staff, and students alike—securely, equitably, and with room to grow. It wasn’t just a chatbot. It was the beginning of an extensible, multimodal AI foundation, deployed inside their own infrastructure, and tailored to the unique needs of higher education.

At the center of it all? FoundationaLLM.

Education use case image 1.

A Platform Built for Equity, Privacy, and Agility

This university’s AI task force had a clear mandate: empower the entire academic community with generative AI—but do it in a way that protected institutional data, aligned with privacy policies, and avoided vendor lock-in.

They didn’t want a SaaS chatbot.

They wanted a secure platform that could grow with them. Something that felt as easy to use as public GenAI tools—but ran inside their own Azure environment, enforced university policies, and gave users the flexibility to explore responsibly.

By the start of the semester, they had it. Built on FoundationaLLM, the university’s internal AI platform offered:

  • Multiple LLMs (including OpenAI and Anthropic) accessible through a unified interface
  • File upload and analysis across over 20 formats, including DOCX, PDF, XLSX, and images
  • Image generation capabilities via DALL·E 3
  • Role-based access to ensure secure use of sensitive or high-risk data
  • No data sharing with external model providers—everything remained governed in-place

This wasn’t just an IT win. It was a strategic leap forward for the university—giving students, faculty, and staff a way to interact with powerful GenAI tools without compromising academic integrity, data security, or accessibility.

Education use case image 2.

Delivering Real Value, Faster—and at Lower Cost

For most institutions, building this kind of AI infrastructure would take a year or more—and require hiring a dedicated team of developers, ML engineers, and AI product managers.

With FoundationaLLM, the university was able to move fast without making compromises:

  • Platform deployed within weeks, with no need to build from scratch
  • Out-of-the-box agents provided immediate functionality for writing, summarization, coding support, and more
  • Custom agents could be created easily with no-code or low-code interfaces
  • Deployed directly in the university’s Azure environment, ensuring full control and compliance

The result? A dramatically lower total cost of ownership (TCO), faster time to value, and no need to staff up just to keep the system running.

The university’s internal teams could stay focused on training, enablement, and future innovation—instead of wrangling APIs or building scaffolding from scratch.

Use Cases Beyond the Classroom

While the initial goal was equitable access to AI for everyday academic tasks, the platform unlocked broader opportunities across the university. With FoundationaLLM, institutions can expand use cases at their own pace—without needing to re-architect the system.

Examples include:

  • Faculty Agents: Department-specific agents that assist with grading, curriculum design, or summarizing research literature
  • Administrative Tools: AI assistants that help staff analyze enrollment trends, summarize budget docs, or process incoming requests
  • Student Support Bots: Agents trained on academic policies, campus resources, and syllabi to provide real-time answers without overloading support staff
  • Secure Research Assistants: Tools that help researchers navigate datasets, summarize findings, or draft publications—without sending data off-platform

Each of these agents can be built, governed, and deployed inside the same FoundationaLLM instance—no new infrastructure needed.

Education use case image 3.

Why It Works: Platform, Not Point Solution

FoundationaLLM isn’t a chatbot builder. It’s a full-stack AI platform designed for scalable, secure, enterprise-grade deployments. For universities, that means:

  • Runs in your Azure environment (not a SaaS product—no vendor lock-in, full control)
  • Compatible with any major LLM, vector store, or data source
  • Governed by RBAC and policy-based controls at every layer
  • Extensible agent architecture that makes it easy to add new use cases over time
  • Stays current with the fast-changing AI landscape, acting as an R&D team without the cost or risk of maintaining bleeding-edge expertise in-house

From user provisioning to quota enforcement to content safety, FoundationaLLM is built to meet the demands of large, decentralized environments like higher education institutions.

And because it’s easy for both technical and non-technical users to interact with, adoption doesn’t require a full-time AI team to maintain.

What’s Next for AI in Education?

This university’s journey shows what’s possible when you pair the right vision with the right platform. They didn’t wait for a perfect tool—they partnered with FoundationaLLM to build what they needed, securely and sustainably.

Whether your institution is just starting to explore GenAI or ready to go beyond proof of concept, FoundationaLLM is designed to help you get there faster, at lower cost, and with the confidence that comes from owning the deployment end-to-end.

See How Fast You Can Move

Explore how FoundationaLLM can support your institution’s AI journey—without compromising on governance, usability, or innovation.

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